Protein Interactome Analysis of the Type IX Secretion System Identifies PorW as the Missing Link between the PorK/N Ring Complex and the Sov Translocon

The T9SS is a newly identified protein secretion system of the Fibrobacteres - Chlorobi - Bacteroidetes superphylum used by pathogens associated with diseases of humans, fish, and poultry for the secretion and cell surface attachment of virulence factors. The T9SS comprises three known modules: (i) the trans-envelope core module comprising the PorL/M motor and the PorK/N ring, (ii) the outer membrane Sov translocon, and (iii) the cell surface attachment complex.

Automated Recognition of Chemical Molecule Images Based on an Improved TNT Model

The automated recognition of optical chemical structures, with the help of machine learning, could speed up research and development efforts. However, historical sources often have some level of image corruption, which reduces the performance to near zero. To solve this downside, we need a dependable algorithmic program to help chemists to further expand their research. This paper reports the results of research conducted for the Bristol-Myers Squibb-Molecular Translation competition, which was held on Kaggle and which invited participants to convert old chemical images to their underlying chemical structures, annotated as InChI text; we define this work as molecular translation. We proposed a model based on a transformer, which can be utilized in molecular translation. To better capture the details of the chemical structure, the image features we want to extract need to be accurate at the pixel level. TNT is one of the existing transformer models that can meet this requirement. This model was originally used for image classification, and is essentially a transformer-encoder, which cannot be utilized for generation tasks. On the other hand, we believe that TNT cannot integrate the local information of images well, so we improve the core module of TNT—TNT block—and propose a novel module—Deep TNT block—by stacking the module to form an encoder structure, and then use the vanilla transformer-decoder as a decoder, forming a chemical formula generation model based on the encoder–decoder structure. Since molecular translation is an image-captioning task, we named it the Image Captioning Model based on Deep TNT (ICMDT). A comparison with different models shows that our model has benefits in each convergence speed and final description accuracy. We have designed a complete process in the model inference and fusion phase to further enhance the final results.

Object segmentation in cluttered environment based on gaze tracing and gaze blinking

People with disabilities, such as patients with motor paralysis conditions, lack independence and cannot move most parts of their bodies except for their eyes. Supportive robot technology is highly beneficial in supporting these types of patients. We propose a gaze-informed location-based (or gaze-based) object segmentation, which is a core module of successful patient-robot interaction in an object-search task (i.e., a situation when a robot has to search for and deliver a target object to the patient). We have introduced the concepts of gaze tracing (GT) and gaze blinking (GB), which are integrated into our proposed object segmentation technique, to yield the benefit of an accurate visual segmentation of unknown objects in a complex scene. Gaze tracing information can be used as a clue as to where the target object is located in a scene. Then, gaze blinking can be used to confirm the position of the target object. The effectiveness of our proposed method has been demonstrated using a humanoid robot in experiments with different types of highly cluttered scenes. Based on the limited gaze guidance from the user, we achieved an 85% F-score of unknown object segmentation in an unknown environment.

Structure of the human SAGA coactivator complex

The SAGA complex is a regulatory hub involved in gene regulation, chromatin modification, DNA damage repair and signaling. While structures of yeast SAGA (ySAGA) have been reported, there are noteworthy functional and compositional differences for this complex in metazoans. Here we present the cryogenic-electron microscopy (cryo-EM) structure of human SAGA (hSAGA) and show how the arrangement of distinct structural elements results in a globally divergent organization from that of yeast, with a different interface tethering the core module to the TRRAP subunit, resulting in a dramatically altered geometry of functional elements and with the integration of a metazoan-specific splicing module. Our hSAGA structure reveals the presence of an inositol hexakisphosphate (InsP6) binding site in TRRAP and an unusual property of its pseudo-(Ψ)PIKK. Finally, we map human disease mutations, thus providing the needed framework for structure-guided drug design of this important therapeutic target for human developmental diseases and cancer.

The SAGA core module is critical during Drosophila oogenesis and is broadly recruited to promoters

The Spt/Ada-Gcn5 Acetyltransferase (SAGA) coactivator complex has multiple modules with different enzymatic and non-enzymatic functions. How each module contributes to gene expression is not well understood. During Drosophila oogenesis, the enzymatic functions are not equally required, which may indicate that different genes require different enzymatic functions. An analogy for this phenomenon is the handyman principle: while a handyman has many tools, which tool he uses depends on what requires maintenance. Here we analyzed the role of the non-enzymatic core module during Drosophila oogenesis, which interacts with TBP. We show that depletion of SAGA-specific core subunits blocked egg chamber development at earlier stages than depletion of enzymatic subunits. These results, as well as additional genetic analyses, point to an interaction with TBP and suggest a differential role of SAGA modules at different promoter types. However, SAGA subunits co-occupied all promoter types of active genes in ChIP-seq and ChIP-nexus experiments, and the complex was not specifically associated with distinct promoter types in the ovary. The high-resolution genomic binding profiles were congruent with SAGA recruitment by activators upstream of the start site, and retention on chromatin by interactions with modified histones downstream of the start site. Our data illustrate that a distinct genetic requirement for specific components may conceal the fact that the entire complex is physically present and suggests that the biological context defines which module functions are critical.

Point-of-Care Biomedical Engineering Equipment Management System

BackgroundMedical devices and equipment play an important role in the modern medical service. It is necessary to integrate the relevant information in order to effectively manage all the equipment into a biomedical engineering equipment management system (BEEMS). Aims: To report our experience and satisfactory from the users of a BEEMS.MethodWe combine a central core module with intra-net and a mobile device application with internet to become a real-time BEEMS. With the combination of these two modules, the point-of-care software system become real-time and mobile for all users in the hospital. We conduct a survey about satisfactory from the users after more than one-year implementation of this system. ResultsAfter the application more than one year, only 7% users show unsatisfactory about the BEEMS. We also find this real-time and point-of-care BEEMS has high satisfactory and is especial helpful for the management staff in hospital. ConclusionA real-time BEEMS has high satisfactory and is helpful for the staff in hospital.Relevance to clinical practiceA real-time biomedical engineering equipment management system is helpful to effectively manage all the equipment in hospital.

Ultrafast Photoconversion Dynamics of the Knotless Phytochrome SynCph2

The family of phytochrome photoreceptors contains proteins with different domain architectures and spectral properties. Knotless phytochromes are one of the three main subgroups classified by their distinct lack of the PAS domain in their photosensory core module, which is in contrast to the canonical PAS-GAF-PHY array. Despite intensive research on the ultrafast photodynamics of phytochromes, little is known about the primary kinetics in knotless phytochromes. Here, we present the ultrafast Pr ⇆ Pfr photodynamics of SynCph2, the best-known knotless phytochrome. Our results show that the excited state lifetime of Pr* (~200 ps) is similar to bacteriophytochromes, but much longer than in most canonical phytochromes. We assign the slow Pr* kinetics to relaxation processes of the chromophore-binding pocket that controls the bilin chromophore’s isomerization step. The Pfr photoconversion dynamics starts with a faster excited state relaxation than in canonical phytochromes, but, despite the differences in the respective domain architectures, proceeds via similar ground state intermediate steps up to Meta-F. Based on our observations, we propose that the kinetic features and overall dynamics of the ultrafast photoreaction are determined to a great extent by the geometrical context (i.e., available space and flexibility) within the binding pocket, while the general reaction steps following the photoexcitation are most likely conserved among the red/far-red phytochromes.

Melatonin Alleviates Low-Temperature Stress via ABI5-Mediated Signals During Seed Germination in Rice (Oryza sativa L.)

With increasing areas of direct sowing, low-temperature (LT) stress drastically affects global rice production. Exogenous applications of melatonin (MT) serve as one of the effective ways to improve seed germination under various stress conditions. In this study, we found that MT treatment greatly improved the LT stress-induced loss of germination percentage and the weak performance of seedlings under LT of constant 20°C (LT20). This was largely dependent on the activated antioxidant system and enhanced activities of storage substance utilization-associated enzymes. Moreover, we also detected that exogenous feeding of MT significantly increased the biosynthesis of gibberellin (GA) and endogenous MT but simultaneously inhibited the accumulation of abscisic acid (ABA) and hydrogen peroxide (H2O2) under LT20 stress. These results suggested that MT had antagonistic effects on ABA and H2O2. In addition, MT treatment also significantly enhanced the expression of CATALYSE 2 (OsCAT2), which was directly regulated by ABA-INSENSITIVE 5 (OsABI5), a core module of ABA-stressed signals, and thus promoting the H2O2 scavenging to reach reactive oxygen species (ROS) homeostasis, which consequently increased GA biosynthesis. However, in abi5 mutants, OsCAT2 failed in response to LT20 stress irrespective of MT treatment, indicating that OsABI5 is essential for MT-mediated seed germination under LT20 stress. Collectively, we now demonstrated that MT showed a synergistic interaction with an ABI5-mediated signal to mediate seed germination, partially through the direct regulation of OsCAT2.

Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization

Meeting summarization is a challenging task due to its dynamic interaction nature among multiple speakers and lack of sufficient training data. Existing methods view the meeting as a linear sequence of utterances while ignoring the diverse relations between each utterance. Besides, the limited labeled data further hinders the ability of data-hungry neural models. In this paper, we try to mitigate the above challenges by introducing dialogue-discourse relations. First, we present a Dialogue Discourse-Dware Meeting Summarizer (DDAMS) to explicitly model the interaction between utterances in a meeting by modeling different discourse relations. The core module is a relational graph encoder, where the utterances and discourse relations are modeled in a graph interaction manner. Moreover, we devise a Dialogue Discourse-Aware Data Augmentation (DDADA) strategy to construct a pseudo-summarization corpus from existing input meetings, which is 20 times larger than the original dataset and can be used to pretrain DDAMS. Experimental results on AMI and ICSI meeting datasets show that our full system can achieve SOTA performance. Our codes and outputs are available at https://github.com/xcfcode/DDAMS/.